Data Engineer

cisco

Hyderabad 4 Years Exp Posted 12d ago

Job Description

  • Design, build, and maintain Power BI reports, datasets, and semantic models supporting NPS, TAC case analytics, EBV/EDW reconciliation, and customer health measurement.
  • Develop and manage Power Automate workflows for automated insight delivery, including integration with AI-generated summary pipelines (GCP ESPv2 / API Gateway).
  • Author and maintain DAX measures, calculation groups, and field parameters for complex, hierarchy-driven reporting across SAV, CAV, and UNIFIED_PARTY_ID structures.
  • Collaborate with data engineering team members on Snowflake query optimization and dbt layer consumption, identifying and resolving model-layer issues that surface in report outputs.
  • Partner with the broader analytics team to instrument parametric, configurable dashboard layers that support plug-and-play organizational hierarchy switching without requiring report rebuilds.
  • Contribute to the team’s Microsoft Fabric readiness strategy, evaluating Direct Lake mode and OneLake integration patterns as the organization transitions its BI architecture.
  • Provide thought leadership on AI-augmented analytics—including Copilot in Power BI, AI visuals, and LLM-integrated insight surfaces—aligned to the VP directive on AI future-readiness.

 

Minimum Qualifications

 

  • 4+ years of hands-on Power BI development experience, including advanced DAX authoring, RLS implementation, incremental refresh configuration, and deployment pipeline management.
  • Demonstrated experience designing and building Power Automate workflows that integrate with external APIs or cloud services for automated data delivery or alert distribution.
  • Working proficiency in SQL with demonstrated ability to query and consume data from cloud data warehouses (Snowflake strongly preferred), including multi-level hierarchical aggregation patterns.
  • Experience building and maintaining semantic data models (star or snowflake schema) that support multi-dimensional analytical reporting at enterprise scale.
    • Foundational Python skills sufficient for data wrangling, parameterization scripting, or preprocessing tasks within an analytics pipeline context.

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